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Dr Saeed Akhlaghpour is an Associate Professor of Information Systems at UQ Business School. Prior to joining the University of Queensland in 2015, he held academic positions at Middlesex University London (UK), and McGill University (Canada) - where he also obtained his PhD in Management.

Saeed is a Fellow of the Higher Education Academy. He teaches Information Systems, Artificial Intelligence (AI), and digital strategy and governance in the Master of Business Analytics, Master of Commerce, MBA, and Executive Education programs. Previously, he has taught courses to MBA and undergraduate business students in Brisbane, London, Montreal, and Tehran.

Saeed’s research has been published in top-tier academic outlets, including the American Journal of Sociology, Journal of the Association for Information Systems, Journal of Information Technology, Information and Organization, Journal of the American Medical Informatics Association, International Journal of Medical Informatics, International Journal of Information Management, Journal of Business Research, and the Best Paper Proceedings of Academy of Management. His articles are cited in the EU policy documents and have received research and impact awards from the Administrative Sciences Association of Canada, and the Australasian chapter of the Association for Information Systems (AIS).

His research interests include:

• Data protection, privacy, and cybersecurity (particularly, organisational response to data breaches, and managing personal health information (PHI))
• Digital health and transformation of healthcare services
• Diffusion, adoption, and governance of digital innovations (particularly, Enterprise Generative AI)

Saeed has been a Chief Investigator in an Australian Research Council (ARC) funded Linkage Project studying Digital Hospital implementation in Queensland hospitals and health services. He received the UQ Business School Cross Cross-Disciplinary Research Award in 2021. He is a founding member of the Future of Health and Trust, Ethics, and Governance Alliance research hubs.

He is a Guest Editor of Information and Organization, Section Editor of the Australasian Journal of Information Systems, Associate Editor of the Asia Pacific Journal of Information Systems (APJIS), and Editorial Board member of the International Journal of Medical Informatics. He chairs the annual DIGIT Workshop of the Special Interest Group on Adoption and Diffusion of Information Technology (SIG ADIT) and co-chairs the Digital Health Care track at the Australasian Conference on Information Systems (ACIS). He has co-chaired tracks at the International Conference on Information Systems (ICIS) and the Pacific Asia Conference on Information Systems (PACIS).

Prof David Ascher is an NHMRC Investigator Leadership Fellow and Deputy Associate Dean (Research Partnerships) in the Faculty of Science at The University of Queensland. He also serves as Deputy Director of the Australian Centre for Ecogenomics and Head of Computational Biology & Clinical Informatics at the Baker Heart and Diabetes Institute. Internationally, he sits on scientific advisory boards for A*STAR (Singapore), Fiocruz (Brazil) and the Tuscany University Network (Italy), and has been recognised with major honours including the Royal Society of Chemistry Horizon Prize.

A global leader in computational biology and personalised medicine, Prof Ascher develops advanced AI- and structure-based approaches to understand how genetic variation alters protein structure, function, and clinical outcomes. His group has built one of the world’s most widely used platforms for interpreting coding variants—over 90 computational tools, accessed more than 9.5 million times per year from 120+ countries. These tools underpin clinical diagnostics, guide drug development pipelines, and support international public-health responses to antimicrobial resistance and emerging infectious diseases.

His research has led to new molecular insights across infectious disease, rare disease, oncology and cardiometabolic health, and has been translated directly into practice—informing WHO policy, enabling early resistance detection in tuberculosis and leprosy, stratifying patients with hereditary cancers, and supporting vaccine design with partners including Pfizer. Many of his methods are embedded in globally used resources such as Ensembl VEP, PDBe, and the EMBL-EBI KnowledgeBase.

Prof Ascher has a longstanding commitment to interdisciplinary leadership and capability-building across UQ. As Director (Strategy) of the Biotechnology Programs and later as Deputy Associate Dean (Research Partnerships), he has driven initiatives to transform UQ’s biotechnology education, grow industry-embedded training, expand international partnerships, and diversify research income. He has led the development of UQ’s biotechnology–industry placement ecosystem, initiated new professional development programs adopted across multiple Faculties and Institutes, and established major collaborations with government, industry and global research organisations.

He has published more than 250 peer-reviewed papers (over half as senior author: FWCI 2.7), secured more than $30M in competitive research funding, and supervised over 60 HDR students who now hold leadership positions in academia, industry and government. His work appears in leading journals including Nature, Nature Genetics, Science, PNAS and Nature Microbiology, and is cited in over 100 policy documents and 40 patents.

Prof Ascher holds degrees in Biotechnology, Biochemistry, Structural Biology and Law. His research career has spanned Adelaide, Melbourne, Cambridge and Brisbane. After his PhD with Professor Michael Parker, he worked with Sir Tom Blundell at the University of Cambridge, where he led programs in structure-guided drug discovery and protein–protein interaction targeting. He established his independent laboratory at Cambridge and then at the University of Melbourne/Bio21 Institute, before moving to the Baker Institute in 2019 and joining UQ in 2021.

Mikael Bodén has a PhD in Computer Science and statistical machine learning from the University of Exeter (UK) but has spent the last decade and a half in biological research environments, including the Institute for Molecular Bioscience/ARC Centre of Excellence in Bioinformatics and the School of Chemistry and Molecular Biosciences, where he is currently located. He is the director of UQ’s postgraduate program in bioinformatics. Mikael Bodén has supervised 7 postdocs from funding he received from both ARC and NHMRC; he has been the primary advisor for 11 PhD and 3 MPhil graduates; he is currently supervising another 6 PhD students in bioinformatics and computational biology. Mikael Bodén collaborates with researchers in neuroscience, developmental biology, protein engineering and bioeconomy to mention but a few, and contributes expertise in the processing, analysis and integration of biological data; this is exemplified by recent publications in Science, Nature Catalysis, Nature Communications, Cell Systems, Nucleic Acids Research and Bioinformatics.

Dr Steffen Bollmann joined UQ’s School of Electrical Imaging and Computer Science in 2020 where he leads the Computational Imaging Group. The Group is developing computational methods to extract clinical and biological insights from magnetic resonance imaging (MRI) data. The aim is to make cutting-edge algorithms and tools available to a wide range of clinicians and researchers. This will enable better images, faster reconstruction times and the efficient extraction of clinical information to ensure a better understanding of a range of diseases. Dr Bollmann was appointed Artificial Intelligence (AI) lead for imaging at UQ’s Queensland Digital Health Centre (QDHeC) in 2023.

His research expertise is in quantitative susceptibility mapping, image segmentation and software applications to help researchers and clinicians access data and algorithms.

Dr Bollmann completed his PhD on multimodal imaging at the University Children’s Hospital and Swiss Federal Institute of Technology (ETH) Zurich, Switzerland.

In 2014 he joined the Centre for Advanced Imaging at UQ as a National Imaging Facility Fellow, where he pioneered the application of deep learning methods for quantitative imaging techniques, in particular Quantitative Susceptibility Mapping.

In 2019 he joined the Siemens Healthineers collaborations team at the MGH Martinos Center in Boston on a one-year industry exchange where he worked on the translation of fast imaging techniques into clinical applications.

Shakes an imaging expert that leads a strong deep learning, artificial intelligence (AI) focused research team interested in medical image analysis and signal/image processing applied to many areas of science and medicine. He received his Ph.D in Theoretical Physics from Monash University, Melbourne and has been involved in applying machine learning in medical imaging for over a decade.

Shakes’ past work has involved developing shape model-based algorithms for knee, hip and shoulder joint segmentation that is being developed and deployed as a product on the Siemens syngo.via platform. More recent work involves deep learning based algorithms for semantic segmentation and manifold learning of imaging data. Broadly, he is interested in understanding and developing the mathematical basis of imaging, image analysis algorithms and physical systems. He has developed algorithms that utilise exotic mathematical structures such as fractals, turbulence, group theoretic concepts and number theory in the image processing approaches that he has developed.

He is currently a Senior Lecturer and leads a team of 20+ researchers working image analysis and AI research across healthcare and medicine. He currently teaches the computer science courses Theory of Computation and Pattern Recognition and Analysis.

Dr Archie Chapman is an Associate Professor in Computer Science in the School of IT and Electrical Engineering.

Archie develops and applies principled artificial intelligence, game theory, optimisation and machine learning methods to solve large-scale and dynamic allocation, scheduling and queuing problems. His recent research has focused on applications of these techniques to problems in future power systems, such as integrating large amounts of renewable power generation and using batteries and flexible loads to provide power network and system services, while making best use of legacy network and generation infrastructure.

Prior to joining UQ, Archie was Research Fellow in Smart Grids at the University of Sydney (2011-2019), and a postdoc fellow at the University of Southampton (2009-2010), where he completed his PhD.

Summary of Research:

• My current research at UQ is as Professor in this School (teaching AGRC3040 Crop Physiology) and as an Affiliate Professor of QAAFI. Since 2020, with full-time appointment at UQ, my research portfolio has included multiple projects in applications of machine learning and artificial intelligence into the ag domain. This area is developing rapidly and across UQ, I am engaging with faculty in multiple schools (ITEE, Maths and Physics, Mining and Mech Engineering) as well as in the Research Computing Centre to develop new projects and training opportunities at the interface of field agriculture and these new digital analytics.
• My career research has been around genetic and environment effects on physiology of field crops, particularly where drought dominates. Application of quantitative approaches (crop simulation and statistical methods) and phenotyping (aerial imaging, canopy monitoring) to integrate the understanding of interactions of genetics, growth and development and the bio-physical environment on crop yield. In recent years, this work has expanded more generally into various applications in digital agriculture from work on canopy temperature sensing for irrigation decisions (CSIRO Entrepreneurship Award 2022) through to applications of deep-learning to imagery to assist breeding programs.
• Much of this research was undertaken with CSIRO since 1996. Building on an almost continuous collaboration with UQ over that time, including as an Adjunct Professor to QAAFI, Prof Chapman was jointly appointed (50%) as a Professor in Crop Physiology in the UQ School of Agriculture and Food Sciences from 2017 to 2020, and at 100% with UQ from Sep 2020. He has led numerous research projects that impact local and global public and private breeding programs in wheat, sorghum, sunflower and sugarcane; led a national research program on research in ‘Climate-Ready Cereals’ in the early 2010s; and was one of the first researchers to deploy UAV technologies to monitor plant breeding programs. Current projects include a US DoE project with Purdue University, and multiple projects with CSIRO, U Adelaide, La Trobe, INRA (France) and U Tokyo. With > 8500 citations, Prof Chapman is currently in the top 1% of authors cited in the ESI fields of Plant and Animal Sciences and in Agricultural Sciences.

Jen Jen Chung is an Associate Professor in Mechatronics within the School of Electrical Engineering and Computer Science at The University of Queensland. Her current research interests include perception, planning and learning for robotic mobile manipulation, algorithms for robot navigation through human crowds, informative path planning and adaptive sampling. Prior to working at UQ, Jen Jen was a Senior Researcher in the Autonomous Systems Lab (ASL) at ETH Zürich from 2018-2022 and was a Postdoctoral Scholar at Oregon State University researching multiagent learning methods from 2014-2017. She completed her Ph.D. on information-based exploration-exploitation strategies for autonomous soaring platforms at the Australian Centre for Field Robotics in the University of Sydney. She received her Ph.D. (2014) and B.E. (2010) from the University of Sydney.

Shane Culpepper is a Professor of Artificial Intelligence at the University of Queensland in St. Lucia, Australia. Before joining the University of Queensland in 2023, Professor Culpepper held a continuing academic position at RMIT University in Melbourne, Australia. He received his PhD in Computer Science from the University of Melbourne in 2008. His research focuses primarily on building better Search and Recommendation Systems and is primarily interested how to responsibly integrate efficient and scalable generative AI models for search, recommendation, and question answering. Professor Culpepper’s work has applications in a number of downstream applications for Legal, Health, real estate speculation. He has been instrumental in founding the AI Research Network and the Research Center for Enterprise AI at the University of Queensland.

Over his 17 year career, Professor Culpepper has supervised 19 PhD students and co-authored more than 140 peer reviewed papers with 132 different research collaborators on problems that range from core basic research, such as algorithm efficiency and scalability, to practical real world problems on building and deploying new machine learning algorithms for search and recommendation systems. While often technical, his work is always user-driven as humans are the main consumers of this technology. This user-centric research focus has led to several papers on controlled user studies which guide the development of better evaluation techniques which model human behaviour. In the last 5 years, Professor Culpepper has been a program co-chair for international conferences such as SIGIR and CIKM, and co-organized conferences such as WSDM and SWIRL. Professor Culpepper previously held an ARC DECRA fellowship in 2013 as well as an RMIT Vice-Chancellor's Principal Researcher fellowship in 2017. Before joining the University of Queensland. Professor Culpepper was the founding director of the Centre for Information Discovery and Data Analytics at RMIT University. In total, he has been a chief investigator on 11 research grants totalling ~$3.8 Million AUD.

Pratap is an IP Strategist and Patent researcher. He has expertise in dealing with Intellectual Property issues in relation to emerging technologies such as Artificial Intelligence (AI), 3D bioprinting and synthetic biology. He is currently a Postdoctoral fellow at TC Bernie School of Law, University of Queensland, Australia. Pratap pursued his PhD from the Centre for Law and Genetics, University of Tasmania, Australia where his research was focused on "Patenting issues related to Bioprinted tissues and Bioinks." In 2018, he was invited by Govt. of Japan to assist the Japanese Patent Office (JPO) in harmonizing Japanese Patent Law in relation to AI. In 2017, he completed his Master of Law (LLM) in Intellectual Property from the World Intellectual Property Organization (WIPO), Geneva and the Queensland University of Technology, Australia. He is the recipient of the prestigious International Fellowship offered by WIPO. He holds a Master's degree in Genomics from the Central University of Kerala, India and a Bachelor’s degree in Biotechnology, Microbiology, and Chemistry from Acharya Nagarjuna University, India. Pratap also holds a Postgraduate Diploma in Patent informatics from the Academy of Scientific and Innovative Research (AcSIR) at the CSIR Unit of Research and Development of Information Products (URDIP), India and worked as a Patent researcher in the same.

Gordon holds a PhD in Chemical Engineering from the University of Cape Town, South Africa, which focused on the application of machine vision, image processing and machine learning algorithms for modelling grade in froth flotation systems.

Gordon spent ten years working for the Victorian Government developing technical computing and modelling solutions. These included the development of the Environmental Systems Modelling Platform, a tool that aims to bring multiple environmental models and datasets into a single easy to use software package, and the development of the Native Vegetation Regulations Tool, to calculate the interactions between proposed clearings and models of rare and threatened species, and thereby determine the required offset credits. More recently, Gordon worked as a data scientist at the Victorian Centre for Data Insights, where he worked with a team focused on delivering innovative data driven solutions across the government sector.

Gordon now applies his data analytics, modelling and technical computing skills at the JKMRC where he works with the Advanced Process Prediction and Control group developing tools for improved time series analysis and visualisation of industrial data and comminution process models.

Professor Kristen Gibbons is Group Lead of the Children’s Intensive Care Research Program at the Child Health Research Centre, The University of Queensland, Co-Chair of the Australian and New Zealand Intensive Care Society Paediatric Study Group (ANZICS PSG).

Professor Gibbons holds qualifications in mathematics, information technology, biostatistics, and research communication, and completed her PhD in Biostatistics at UQ. Her career has been dedicated to transforming outcomes for critically ill children through the design and delivery of large-scale international clinical trials and the development of innovative digital platforms to support high-quality research.

She has been instrumental in leading landmark studies, including the NITRIC trial, the largest trial ever undertaken in paediatric congenital heart disease surgery. This trial demonstrated no benefit of using nitric oxide during cardiopulmonary bypass, changing clinical practice internationally and influencing guidance from the American Academy of Paediatrics. Alongside this, Professor Gibbons has pioneered a comprehensive clinical trials digital platform now used across more than 20 projects and 10,000 patient records worldwide.

Professor Gibbons’ research spans clinical trial methodologies, epidemiology, machine learning, prediction modelling, and bioethics, with a strong commitment to improving consent practices in paediatric and adult intensive care research. Her leadership has attracted over $22 million in competitive grant funding, including major NHMRC and MRFF awards, and her contributions have been recognised with the UQ Faculty of Medicine Leader of the Future Award (2023) and the Child Health Research Centre Collaborator of the Year Award (2024).

She is also deeply invested in training and mentoring the next generation of clinician-researchers and data scientists, supervising PhD, Masters, and biostatistics students.

Dr Anthony Halog: Expert in Circular Economy, Life Cycle Thinking, and Sustainable Systems

Dr. Anthony B. Halog is a professor at the University of Queensland specialising in circular economy, sustainability engineering, industrial ecology, and life cycle assessment (LCA/LCSA). His current work focuses on designing low-carbon, net-zero, and resource-efficient systems to address climate change, waste reduction, and sustainable development.

Dr. Halog works across energy, materials, food, waste, and policy systems, applying systems thinking, life cycle sustainability assessment, digital twins, and artificial intelligence for sustainability. His research helps governments, industries, and communities make evidence-based decisions that reduce emissions, improve resource efficiency, and avoid unintended environmental impacts.

A core focus of his work is transforming linear value chains into circular value chains, supporting green hydrogen, bioenergy, circular bioeconomy, agricultural waste valorisation, waste-to-energy, and sustainable materials. These solutions contribute to decarbonisation, climate resilience, sustainable supply chains, and the green economy.

Key areas of expertise

• Circular economy and industrial ecology

• Life cycle assessment and sustainability metrics

• Green hydrogen, bioenergy, and clean energy transitions

• Sustainable waste management and circular bioeconomy

• Systems modelling, AI-enabled tools, and sustainability policy

Dr. Halog collaborates with policymakers, industry partners, SMEs, and Indigenous communities in Australia and internationally to deliver practical climate solutions and support the transition to decarbonised circular economies.

I undertake multi-disciplinary collaborative research developing mathematical, computational and visualisation approaches and techniques that facilitate the research and education in animal and plant systems.

My major research theme is development of mathematical, computer graphics and simulation approaches and techniques that facilitate the study of genetics, physiology, morphogenesis and ecology at the scale of cells, individual plants and insects and their components. These developments in computational biology are being used to increase our understanding of the dynamics of morphogenesis, and as a tool in applied research and education.

Dr Leah Henrickson is a Senior Lecturer in Digital Media and Cultures at the University of Queensland. She is the author of Reading Computer-Generated Texts (Cambridge University Press, 2021) and other peer-reviewed articles about how we understand text generation systems and output, artificial intelligence, and digital media environments. Dr Henrickson also studies digital storytelling for critical self-reflection, pedagogy, community building, and commercial benefit. She is the author of Digital Storytelling: An Introduction (Polity, 2025).

Dr Henrickson is an elected member of the Board of Directors for the Society for the History of Authorship, Reading and Publishing (SHARP), and serves on the Editorial Boards of New Review of Hypermedia and Multimedia and Anthem Press' 'Anthem Studies in Book History, Publishing and Print Culture' series. She is also an elected non-professorial member of the University of Queensland's Academic Board.

Dr Henrickson is especially keen to collaborate on projects involving digital methods and media, hermeneutics, histories of communications media, and unconventional text production and dissemination.

MBChB FRCA FANZCA FFICM PhD

Prospective Students

Please visit the link (https://sites.google.com/view/dsteam/pros-students).

Short Biography

Dr. Dan Dongseong Kim is Deputy Director of UQ Cybersecurity and an Associate Professor (Reader in the commonwealth system) (continuing appointment) in Cyber Security at The University of Queensland (UQ), Brisbane, Australia. Before UQ, he was a faculty member (permanent academic staff; Senior Lecturer 2015-2018, Lecturer 2011-2014) in Cyber Security in the Department of Computer Science and Software Engineering at The University of Canterbury (UC), Christchurch, New Zealand from 2011 to 2018. From 2008 to 2011, he was a postdoc at Duke University, Durham, North Carolina in the US. He was a visiting scholar at the University of Maryland, College Park, Maryland in the US in 2007. His research interests are in Cyber Security and Dependability for various systems and networks. Please visit his research team webpage: https://sites.google.com/view/dsteam/

Publications

• Google Scholars (7500+ citations, h-index: 45, i10-index: 127): https://scholar.google.com/citations?user=dIIYVQkAAAAJ&hl=en
• DBLP (200+ publications): https://dblp.org/pid/k/DongSeongKim.html

Research Focus: Cyber G.A.M.E

• Graphical Models for Cyber Security: Model-based Cyber Security Risk Analysis
• AI for Cybersecurity & Cyber Security for AI: Securing AI systems and Cybersecurity using AI
• Moving Target Defense (MTD): Resilient and Proactive Defence
• Evolving Attacks and Defense Automation: Red team and Blue team Automation and evaluation using AI/LLM

Professional Activities (selected)

• Associate Editor, IEEE Communications Surveys and Tutorials (impact factor: 33.84 (2022-2023), #1 impact factor among all the IEEE journals), 2021 - present.
• Editorial Board Member, Elsevier Computers and Security (impact factor: 5.6 (2023)), 2019 - present.
• Editorial Board Member, Elsevier Computer Networks (impact factor: 5.6 (2023)), April 2022 - present.
• An Elected Member of the IFIP WG 10.4 on Dependable Computing and Fault Tolerance (2021 onwards).
  • The IFIP WG 10.4 consists of over 60 experts in the field of fault-tolerance, dependable and secure computing.
• Steering committee member of IFIP/IEEE DSN, 2021-2025.
• Steering committee Chair of IEEE PRDC, 2022-present.
• Steering committee member of IEEE PRDC, 2019-present.
• TPC member of international conferences including IFIP/IEEE DSN, SRDS, ISSRE, ICDCS, etc.

Selected publications

• Securing End-to-End Reinforcement Learning-Driven Autonomous Driving: A Control Command Utility-based Intrusion Response System. IEEE Transactions on Intelligent Vehicles, 2025 [impact factor: 14.3]
• LAGER: Layer-wise Graph Feature Extractor for Network Intrusion Detection, IEEE/IFIP DSN 2025 [CORE A] (best dependability and security conference)
• Adversarial Machine Learning for Network Intrusion Detection Systems: A Comprehensive Survey, IEEE Communications Surveys & Tutorials [Impact factor in 2021: 33.84]
• Toward Proactive, Adaptive Defense: A Survey on Moving Target Defense, IEEE Communications Surveys & Tutorials 2020 [Impact Factor 2018-19: 22.973]
• A Survey on Threat Situation Awareness Systems: Framework, Techniques, and Insights, ACM Computing Surveys, 2022 [Impact Factor 2021-22: 10.282, ranked 4/137 in Computer Science Theory & Methods]
• Evaluating the effectiveness of shuffle and redundancy MTD techniques in the cloud. Computers & Security (2021) [Impact factor: 4.438]
• Threat-Specific Security Risk Evaluation in the Cloud. IEEE Trans. Cloud Comput. 9(2): 793-806 (2021) [Impact factor: 4.714]
• Dynamic Security Metrics for Measuring the Effectiveness of Moving Target Defense Techniques, Computers & Security, Elsevier, 2018 [Impact factor: 4.438]
• Assessing the Effectiveness of Moving Target Defenses using Security Models. IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2016. [CORE Rank A, Impact factor: 6.404]
• Recovery from software failures caused by Mandelbugs. IEEE Transactions on Reliability, 2016. [CORE Rank A, Impact factor: 2.79]
• Scalable Security Models for Assessing Effectiveness of Moving Target Defenses, IEEE/IFIP DSN 2014 [CORE Rank A*]
• Sensitivity Analysis of Server Virtualized System Availability. IEEE Transactions on Reliability, 61(4): 994-1006, 2012. [CORE Rank A, Impact factor: 2.293]
• Scalable Optimal Countermeasure Selection using Implicit Enumeration on Attack Countermeasure Trees, IEEE/IFIP DSN 2012 [CORE Rank A*]

Research Sponsors (past and current)

• NSF (US), IBM T.J. Watson (US), US Army Research Lab./DEVCOM-Pacific (US), NEC (Japan), Tait Comm. (NZ), MBIE (NZ), NPRP (Qatar), ADD (Republic of Korea), NRF (Republic of Korea), etc.

Ph.D. graduates (selected)

1. Ke He (Ph.D., University of Auckland, May 2024, co-supervisor): Adversarial Attacks, Defences and Visualisation for AI-based NIDS. (Lecturer at The University of Canterbury, New Zealanad).

2. Kok Onn Chee (Ph.D., University of Queensland, Jan 2024: Principal Advisor): Security Modelling and Analysis of Internet of Things against Evolving Attacks.

3. Minjune Kim (Ph.D., University of Queensland, 2023: Principal Advisor): Security and performance evaluation of software defined networking adopting moving target defenses (Research Engineer at CSRIO's Data61, Australia).

4. Dilli P. Sharma (Ph.D., University of Canterbury, 2020; senior supervisor at UC, -> co-supervisor at UQ): Software-defined networking based moving target defenses. (Postdoc at U. of New Brunswick, Canada -> Postdoc at the University of Toronto, Canada -> York U., Canada).

5. Taehoon Eom (Ph.D., 2020, KAU, Korea, co-supervisor): Security modeling and analysis for performance enhancement in software defined network (Researcher at KAU-> Research Professor at KAU -> Artificial Intelligence Industry Cluster Agency (AICA), South Korea).

6. Hooman Alavizadeh (Ph.D., Massey University, NZ, 2019, co-supervisor): Effective Security Analysis for Combinations of MTD Techniques on Cloud Computing (a Postdoc, Massey University -> Postdoc at UNSW Canberra->Lecturer at U of Sydney-> Lecturer (continuing academic staff), La Trobe University, Australia).

7. Kieran Morris (Ph.D., ECE, University of Canterbury, NZ, 2019, co-supervisor): Reliability and resilience evaluation of distribution automation (first employment: Tait communications, NZ-> Noted Ltd -> Transpower, NZ).

8. Simon (Enochson) Yusuf (Ph.D., Computer Science, NZ, University of Canterbury, Dec 2018, senior supervisor): Dynamic Cyber Security Modeling and Analysis (Postdoc at UQ-> Lecturer (continuing academic staff) at Federal University Kashere (FUK), Gombe, Nigeria -> Lecturer at Whitecliffe College, New Zealand. )

9. Mengmeng Ge (Ph.D., Computer Science, University of Canterbury, 2018; senior supervisor): Graphical security modeling and assessment for the Internet of things (Lecturer (continuing academic) in Cybersecurity at Deakin University -> RMIT University, Australia -> Deloitte New Zealand-> Senior Lecturer, University of Canterbury, New Zealand-> Senior Lecturer, Monash University, Australia).

10. Iman Elmir (Ph.D., Hassan 1st Univ. Morocco, 2017, co-supervisor): Security Modeling and Analysis of Intrusion Tolerant Data Centers

11. Jin B. Hong (Ph.D., Computer Science, University of Canterbury, April 2015, senior supervisor): Scalable and Adaptable Security Modeling and Analysis. (First employment: Postdoc, UC, NZ -> Lecturer, then Senior Lecturer in Cybersecurity at U of Western Australia)

12. Nguyen Tuan Anh (Ph.D., August 2015, KAU, co-supervisor): Availability Modeling and Analysis of Data Center Systems using Stochastic Reward Nets. (Postdoc, Kunkuk University, South Korea -> an Academic Research Professor, Kunkuk University, South Korea -> Viettel Group, Vietnam)

Cyber Security Research Experience

Dan Dongseong Kim has been working on various topics in computer and network security since 2001. Dan started his research with crypto algorithms design, implementation, and testing for hardware devices such as FPGA/ASICs. Then, he worked on machine learning/data mining approaches for (host-based, network-based) intrusion detection from 2001 onward. His master's thesis was a machine learning (ML)-based network intrusion detection. He worked on various computer and network security topics such as an intelligent SIEM (it was called enterprise security management at that time), authentication protocols for RFID systems, security and privacy for Wireless Sensor Networks (WSNs), etc. His Ph.D. topics were security and privacy for WSNs. He spent one year as a visiting scholar at The University of Maryland (UMD), College Park, Maryland in the US in 2007 under the supervision of Prof. Virgil D. Gligor.

He started working on dependability more seriously in addition to Cyber Security in 2008 when he started his postdoc research at Duke University under the supervision of the Hudson Chaired Professor Kishor S. Trivedi. He worked on research projects funded by the US NSF, NEC Japan, and IBM T.J. Watson in the area of dependability (availability/performance) of data centers/cloud computing and cybersecurity modeling & analysis.

Since he became a faculty member at The University of Canterbury, New Zealand in August 2011, he explored deeply the area of graphical models for cybersecurity, metrics, measurement, and efficient evaluation methods for automated cybersecurity modeling and analysis and applied those key ideas to Cloud computing, Internet of Things (IoT), Moving Target Defenses (MTD), cyber deception, and automated cyber-attacks generation. He has focused more on practical adversarial machine learning attacks and robust defence in network intrusion detection systems for IoT and autonomous vehicles since he joined the UQ in 2019. He worked with diverse groups of people from various countries including Australia, Bangladesh, Brazil, China, Germany, Hong Kong, India, Iran, Italy, Japan, Saudi Arabia, South Korea, Mongolia, Morocco, Malaysia, Nepal, New Zealand, Nigeria, Pakistan, Qatar, USA, UK, and Vietnam.

Academic Genealogy

As for his academic genealogy, his Ph.D. thesis advisor was

• Jong-Sou Park (Pennsylvania State University, Ph.D., 1994); his one was
• Paul Thomas Hulina (Pennsylvania State University, Ph.D., 1969); then it runs back through
• Jon Gustav Bredeson (Northwestern University, Ph.D., 1967),
• Seifollah Louis Hakimi (The University of Illinois at Urbana-Champaign (UIUC), Ph.D., 1959),
• Mac Van Valkenburg (Stanford University, Ph.D., 1952),
• Oswald Garrison Villard, Jr. (Stanford University, Ph.D., 1949),
• Frederick Emmons Terman (widely credited as being the father of Silicon Valley) (Massachusetts Institute of Technology (MIT), 1924, Sc.D.) and
• Vannevar Bush (Jointly Harvard/MIT, D. Eng., 1916) to
• Arthur Edwin Kennelly (Professor at Harvard/MIT) (who was working in Thomas Edison's West Orange Laboratory from December 1887 to March 1894) and Dugald C. Jackson.

His postdoc advisor is Professor Kishor S. Trivedi (UIUC, Ph.D., 1974) who is a Life Fellow of IEEE and the Hudson Distinguished Professor of Electrical and Computer Engineering at Duke University, USA. Please visit the academic tree from Duglad C. Jackson up to the ancestors at the academic tree (link).

Dr Jessica Korte is passionate about the ways good technology can improve lives. To ensure technology is “good”, she advocates involving end users in the design process; especially when those people belong to “difficult” user groups - which usually translates to “minority” user groups. Her philosophy for technology design (and life in general) is that the needs of people who are disempowered or disabled by society should be considered first; everyone else will then benefit from technology that maximises usability. Her research areas include Human-Computer Interaction, Machine Learning, and Participatory & Collaborative Design.

Jessica was drawn to research by a desire to explore some of the ways technology and design can empower and support people from marginalised groups. She has worked with Deaf children and members of the Deaf community to create a technology design approach, and successfully organised and run international workshops on Pushing the Boundaries of Participatory Design, leading to the World’s Most Inclusive Distributed Participatory Design Project.

Jessica has recently been awarded a TAS DCRC Fellowship to create an Auslan Communication Technologies Pipeline, a modular, AI-based Auslan-in, Auslan-out system capable of recognising, processing and producing Auslan signing.

Jessica is currently looking to recruit research students with an interest in exploring topics in an Auslan context, including machine learning, natural language processing, chatbots, video GAN, or procedural animation.

Hang Li is a Research Officer and graduating PhD candidate in IELab within the School of Information Technology and Electrical Engineering at the University of Queensland, Australia, where he works closely with Prof. Guido Zuccon, A/Prof. Bevan Koopman, and Dr. Ahmed Mourad. Prior to Ph.D, Hang received his Bachelor of Science degree in Computer Science at the University of Minnesota Twin-Cities in United States in 2016.

Hang works at the intersection of Information Retrieval (IR), Large Language Models (LLMs), Natural Language Processing (NLP), and Machine Learning (ML) applications, where he utilises different relevance feedbacks to empower the information retrieval system. His recent work seeks to address the gap between relevance feedback, deep language models, and information retrieval through different approaches that helps to improve the IR system effectiveness with minimal efficiency cost.

Hang publishes at premier academic venues in IR (e.g. SIGIR, ECIR, WSDM, WWW, TOIS, IJDL). His work is supported by Grains Research and Development Corporation, through the AgAsk project.

Brian C. Lovell, born in Brisbane, Australia in 1960, received his BE in Electrical Engineering (Honours I) in 1982, BSc in Computer Science in 1983, and PhD in Signal Processing in 1991, all from the University of Queensland (UQ). Currently, he is the Project Leader of the Advanced Surveillance Group at UQ. Professor Lovell served as the President of the International Association of Pattern Recognition from 2008 to 2010, is a Senior Member of the IEEE, a Fellow of the IEAust, Fellow of the Asia-Pacific AI Association, and has been a voting member for Australia on the Governing Board of the International Association for Pattern Recognition since 1998.

He is an Honorary Professor at IIT Guwahati, India; an Associate Editor of the Pattern Recognition Journal; an Associate Editor-in-Chief of the Machine Learning Research Journal; a member of the IAPR TC4 on Biometrics; and a member of the Awards Committee and Education Committee of the IEEE Biometrics Council.

In addition, Professor Lovell has chaired and co-chaired numerous international conferences in the field of pattern recognition, including ICPR2008, ACPR2011, ICIP2013, ICPR2016, and ICPR2020. His Advanced Surveillance Group has collaborated with port, rail, and airport organizations, as well as several national and international agencies, to develop technology-based solutions for operational and security concerns.

His current research projects are in the fields of:

• Artificial Intelligence
• StyleGAN
• Stable Diffusion
• Deep Learning
• Biometrics
• Robust Face Recognition using Deep Learning
• Masked Face Recognition for COVID-19 Pandemic
• Adversarial Attacks on AI Systems
• Digital Pathology
• Neurofibroma Detection and Assessment
• Object Detection with Deep Learning

I am actively recruiting PhD students in Artificial Intelligence to work with my team. If you are interested and have a strong record from a good university, with a publication in a good conference such as CVPR, ICCV, ECCV, or MICCAI please send your CV to me. Full Scholarships (Tuition and Living) can be awarded within one month for truly exceptional candidates.